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Black glutinous rice wine (BGRW) is a traditional Chinese rice wine that is brewed using multiple strains. However, the roles of these microorganisms, particularly their contributions to aroma formation, are poorly understood. Accordingly, the main goal of this study was to determine the microbial communities and major metabolites of different traditional fermentation starters. Anshun (AS) starter and Xingyi (XY) starter were used for BGRW to provide insight into their potential contributions to the variation in flavor and aroma. High-throughput sequencing of the microbial community using the Illumina MiSeq platform revealed significant differences during fermentation between the two starter groups. Pediococcus, Leuconostoc, and Bacillus were the dominant bacterial genera in the AS group, whereas Leuconostoc, Pediococcus, and Gluconobacter were the dominant genera in the XY group. In addition, Rhizopus, Saccharomyces, and Saccharomycopsis were the predominant fungal genera detected in both samples. The major metabolites in the two groups were identified by high-performance liquid chromatography and headspace-solid-phase microextraction gas chromatographymass spectrometry. A total of seven organic acids along with 47 (AS) and 43 (XY) volatile metabolites were detected, among which lactic acid was the primary organic acid, and esters were the largest group in both types of wine. Principal components analysis further revealed significant differences in the dynamic succession of metabolites between the two samples. Correlation analysis showed that 22 and 17 microorganisms were strongly correlated with the production of major metabolites in AS and XY, respectively. Among them, Pediococcus, Leuconostoc, Lactobacillus, Lactococcus, and Streptococcus were shown to play crucial roles in metabolite synthesis. Overall, this study can provide a valuable resource for the further development and utilization of starters to improve the aromatic quality of BGRW.

Panxian ham, a traditional Chinese dry-cured ham, is protected by national geographical indication. Similar to other fermented foods, the microbial population of dry-cured ham is pivotal to taste and flavor formation. This study aimed to establish the relationship between microorganisms and metabolites during the spontaneous fermentation of Panxian ham. Multivariate analysis based on metabolomics data revealed that continuous metabolic changes occurred during the entire fermentation process, with the most significant changes occurring in the initial stage of ripening. Thirty-one significantly different metabolites (SDMs) were identified as discriminant factor, and pathway analysis suggested that these metabolites were involved in 30 pathways, including alanine, aspartate, and glutamate metabolism; glycine, serine, and threonine metabolism; and arginine and proline metabolism. Microbial community analysis using the Illumina MiSeq platform indicated that the bacterial community was more complex than the fungal community, and their succession regulation differed during processing. At the genus level, 11 bacteria and five fungi were identified as core microbes, of which Staphylococcus was the dominant bacteria and Debaryomyces and Aspergillus were the dominant fungi. Further, statistical redundancy analysis (RDA) indicated that Staphylococcus, Debaryomyces, and Chromohalobacter promoted the production of amino and fatty acids; Cobetia and Aspergillus were associated with sugar metabolism, and Kushneria, Penicillium, and Yamadazyma were closely related with organic acids. These findings provide fundamental knowledge regarding the metabolically active microorganisms in Panxian ham, helping industrial processors to develop effective strategies for standardizing quality parameters.

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Pre-fermentation is crucial for black glutinous rice wine production. However, the dynamic changes occurring in metabolites during prefermentation remain unclear. Hence, multivariate analysis to investigate the relationship between metabolites and fermentation time was performed. Both PCA and OPLS-DA score plots showed a typical drift of metabolite profiles during fermentation for 0-60 h, whereas a reverse change occurred after 60 h. Of the 28 significantly different metabolites (SDMs) (VIP > 1 and p < .05) identified during pre-fermentation, 50% were enriched at 60 h including sugar, phenolic acid, and organic acid. This resulted in the highest levels of total phenolic and total acid. Pathway analysis based on SDMs indicated that the starch and sucrose metabolism, alanine, aspartate, and glutamate metabolism, and pentose phosphate pathway were most relevant to pre-fermentation (Pathway impact value > 0.1 and p < .05). The integrated metabolic pathway was generated to understand the transformation and accumulation of SDMs. Metabolite profiles at 0, 60, and 72 h were compared using S-plot. More sugar types were observed at 60 h than at 72 h. Moreover, succinic acid and 4-hydroxyphenylethanol, as metabolites of yeast, were significantly upregulated between 60 and 72 h. Therefore, 60 h is potentially optimal for pre-fermentation of black glutinous rice wine. This study rationalizes the pre-fermentation steps vital for black glutinous rice wine production.

Xiaoqu, one of three traditional jiuqu in China, is a saccharifying and fermenting agent used in Xiaoqu jiu brewing, with different ingredient compositions and preparation techniques used in various regions. The yield and quality of Xiaoqu jiu are significantly affected by the metabolites and microbiota of Xiaoqu; however, the associated relationship remains poorly understood. This study aimed to analyze this relationship in three typical traditional Xiaoqu from the Guizhou province in China. The non-volatile metabolites of Xiaoqu were detected using gas chromatography time-of-flight mass spectrometry, whereas the classification and metabolic potential of the microbiota were investigated using metagenomic sequencing. Results show that Firmicutes, Proteobacteria, and Actinobacteria represent the dominant bacterial phyla, with Lactobacillus, Bacillus, Acinetobacter, Leuconostoc, and Weissella found to be the dominant bacterial genera. Meanwhile, Ascomycota, Mucoromycota, and Basidiomycota are the dominant fungal phyla with Aspergillus, Saccharomyces, Pichia, Rhizopus, and Phycomyces being the predominant fungal genera. Functional annotation of the microbiota revealed a major association with metabolism of carbohydrates, cofactors, and vitamins, as well as amino acids. A total of 39 significantly different metabolites (SDMs) were identified that are involved in 47 metabolic pathways, primarily that of starch and sucrose; glycine, serine, and threonine; glyoxylate and dicarboxylate; pyruvate; as well as biosynthesis of pantothenate and CoA. Further, based on Spearman's correlation analysis, Aspergillus, Saccharomyces, Lactobacillus, Acetobacter, Weissella, Pantoea, Desmospora, and Bacillus are closely correlated with production of physicochemical indexes and SDMs. Moreover, the metabolic network generated for the breakdown of substrates and formation of SDMs in Xiaoqu was found to primarily center on the metabolism of carbohydrates and the tricarboxylic acid cycle. These results provide insights into the functional microorganisms and metabolic patterns present in traditional Guizhou Xiaoqu and might guide researchers in the production of stable and efficient Xiaoqu in the future.

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